Medical Image Understanding and Analysis, Kartoniert / Broschiert

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.- Medical Image Segmentation. .- TransE2UNet: Edge Guided TransEfficientUNET for Generalized Colon Polyp Segmentation from Endoscopy Images. .- CA-Seg: An Attribute-based Medical Image Segmentation Framework for Unified Out-of-distributed Medical Image Segmentation. .- TotalSegmentator 2D: A Tool for Rapid Anatomical Structure Analysis. .- Promptable Cancer Segmentation Using Minimal Expert-curated Data. .- SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver Tumours. .- Semantic Segmentation with Spreading Scribbles. .- A Hybrid Transformer-Graph Model for Multi-Class Lymph Node Segmentation in Histopathology. .- Exploring Context-Switching in Medical Image Retrieval Using Segmentation Models. .- Segmentation in Histopathology Utilising Simulated Masked Patches. .- A Feature-Driven Acquisition Strategy Using Scale-Invariant Descriptors for Deep Active Learning in Preclinical CT Segmentation. .- Quantifying Inter-Annotator Agreement and Generalist Model Limitations in Imaging Mass Cytometry Single Cell Segmentation. .- Subcortical Masks Generation in CT Images via Ensemble-Based Cross-Domain Label Transfer. .- DRASU-Net: Dual-backbone and Residual Atrous Squeeze module-aided U-Net Model for Polyp Segmentation. .- PolypDINO: Adapting DINOv2 for Domain Generalized Polyp Segmentation. .- Intraoperative Segmentation Through Deep Learning and Mask Post-processing in Laparoscopic Liver Surgery. .- Retinal and Vascular Image Analysis. .- Hessian-based Deep Retinal Vessel Segmentation with Extremely Few Annotations. .- Diffusion with Adversarial Fine-Tuning for Improving Rare Retinal Disease Diagnosis. .- Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage. .- Enhanced Coronary Artery Segmentation in CTCA Using Bridging Centreline Integration. .- QD-RetNet: Efficient Retinal Disease Classification via Quantized Knowledge Distillation. .- Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis. .- GenVOG: A Diffusion Probabilistic Framework for Patient-Independent Pose-Guided Nystagmus Video-Oculography (VOG) Generation. .- Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans.